Knowledge that Transforms

This paper investigates how banks utilize soft information to provide contractual flexibility in loan covenant enforcement. We find that relationship lenders are significantly less likely than non‐relationship lenders to enforce covenants for material violations when borrowers are potentially in breach of financial covenants. The mitigation of information asymmetry by relationship lending, as opposed to alternative explanations, serves as the underlying mechanism. Furthermore, relationship borrowers with potential covenant breaches are less likely to experience increases in loan interest rates after renegotiation, to adopt conservative financial or investment policies, or to file for bankruptcy. Following potential covenant breaches of borrowers, relationship banks are better able to preserve regulatory capital and secure future lending business. Our findings suggest that soft information accumulated during lending relationships is vital for banks to provide contractual flexibility.

The study provides large‐scale descriptive evidence on the timing and nature of corporate financial tweeting. Using an unsupervised machine learning approach to analyze 24 million tweets posted by S&P 1500 firms from 2012 to 2020, we find that firms are more likely to tweet financial information around significantly negative or positive news events, such as earnings announcements and the filing of financial statements. This convex U‐shaped relation between the likelihood of posting financial tweets and the materiality of accounting events becomes stronger over time. Whereas research based on early samples concludes that firms are less likely to disseminate financial information on Twitter when the news is bad and material, the symmetric dissemination behavior we find suggests that these conclusions should be revised. We also show that a machine learning algorithm (Twitter‐Latent Dirichlet Allocation) is superior to a dictionary approach in classifying short messages like tweets.

Distributed, rather than co‐located, teams increasingly perform audit work, raising regulator concerns that distributed team communication issues may affect audit quality. We investigate upward communication (i.e., raising issues to supervisors), a key communication dimension related to audit quality. In Study 1, we survey 69 senior auditors to establish that distributed team upward communication suffers. Furthermore, distributed team auditors identify less with their teams and struggle to know when and how to speak up. Because both are linked to inhibited upward communication, we next experimentally test firm practices with the potential to attenuate these problems. Study 2, an experiment with 128 staff auditors and interns, reveals that making auditors' professional identities salient improves upward communication on co‐located teams with strong team identities but not on distributed teams with weak team identities. Study 3, an experiment with 58 staff auditors, replicates a key Study 2 finding with a design that makes no reference to team identity strength. Specifically, in the presence of a salient professional identity, upward communication is significantly higher for co‐located relative to distributed team auditors. Study 4, an experiment with 69 staff auditors, focuses solely on distributed teams. It indicates that several distributed team management practices, including one‐on‐one and standing daily meetings, encourage upward communication. Finally, Study 5, informal interviews with eight audit seniors, corroborates key survey and experimental findings. Combined, our results provide insights into why distributed team communication suffers, refine audit voice theory, and provide regulators, practitioners, and researchers with multiple paths to improve audit quality.

Previous research on calculative intermediaries shows how these effectively challenge, distort, and disrupt accounting practices in ways that policy‐makers might not anticipate. The promises of surveillance capitalism—with its attendant data architectures, datafication processes, and technological sophistication—are different, supposing more accurate ways of reading individuals and greater calculative certainty overall. Yet there is little empirical research to explore how surveillance capitalism manifests itself at the organizational level, either conceptually or operationally. As a result, it remains uncertain whether such specters of omniscience are as haunting in reality as they appear in theory. We explore these themes by way of an ethnographic study into credit scoring in China, showing how intermediary organizations developed a multiplicity of credit scoring models based on machine learning and big data that differed both from original expectations and from each other. These different “renditions” of credit scoring suggest that the data architectures of surveillance capitalism are just as much subject to challenge and adaptation by intermediary organizations as calculative practices, such as accounting, are in more analog environments.

Regulators have raised concerns about the quality of component auditors' work. Of particular concern is that component auditors often do not adequately perform procedures and gather enough quality evidence. This failure is likely caused by component auditors' different interpretations of lead auditor instructions and by their lack of responsibility. Our interview findings suggest that component auditors tend to interpret lead auditor instructions concretely because they often receive detailed instructions from lead auditors. We propose that a responsibility prompt reminding component auditors to be aware of their obligations to the group audit engagement can improve their evidence collection. In two experiments, we find that our proposed responsibility prompt can effectively improve component auditors' evidence collection decisions and that this finding holds across different cultural settings. Our third experiment provides evidence that a responsibility prompt improves component auditors' evidence collection when provided to auditors who receive instructions that prime low‐level (but not high‐level) construals. Overall, our findings suggest that prompting component auditors to internalize the responsibility of a group audit engagement is a viable way to improve the quality of group audits.

Given that tax‐related critical audit matters (tax CAMs) were prevalent among accelerated filers (18.5% of observations) during the initial year of CAM disclosures, we examine whether an auditor's disclosure of tax CAMs is associated with variation in tax‐related financial reporting quality, tax avoidance, and tax‐related earnings management. Finding an association between tax CAMs and one of these tax outcomes would indicate that the new auditor reporting standard has indirectly affected investors. Examining the first year of CAM disclosures, we do not find that tax CAMs are associated with broad proxies of tax‐related audit or financial reporting quality (e.g., restatements, internal control weaknesses, comment letters) or tax avoidance (e.g., effective tax rates or book‐to‐tax differences). We do find that tax CAMs are associated with a modest increase in tax accrual quality, an increase in the reserve for unrecognized tax benefits, and a reduction in the likelihood of tax‐related earnings management. However, we do not find these tax CAM effects persist into the second year of CAM reporting. Our evidence is consistent with tax CAM disclosures having a modest but short‐lived effect on companies' reporting of tax accounts. Our findings should inform the PCAOB as they conduct their post‐implementation review of the new audit reporting standard.

This study extends extant research on the determinants of financial analyst bias by examining the role that political incentives play. Using a series of scheduled provincial political events in China, we document that analysts are significantly more likely to issue favorable recommendations or revise their recommendations upward during political event periods, and the effect of political events on optimism is larger for analysts employed by brokerage firms affiliated with politicians. Cross‐sectional evidence suggests that the impact of political events on analyst optimism is concentrated in those provinces where capital market development is a more important performance indicator for politicians or where the incumbent politicians face a pending promotion. Stock return analyses reveal that favorable recommendations issued during political event periods are significantly less profitable in the long run and are less credible according to investor perceptions. Reinforcing our main evidence, we also find that financial analysts are more likely to issue optimistic earnings forecasts during political event periods. Collectively, our results imply that political incentives distort analyst opinions and political‐economic factors affect the corporate information environment in China.

Exploiting mergers between lenders and shareholders of the same firm as an exogenous shock to shareholder–creditor conflicts, we examine the causal effect of these conflicts on firms' ex ante expected stock price crash risk evident in the options implied volatility smirk. The decrease in conflicts of interest between lenders and shareholders induces dual holders to encourage the disclosure of more information to alleviate costly information asymmetry with other investors and better execute their oversight role in constraining managers' bad news suppression. Consistent with expectations, we find that a firm's ex ante expected crash risk declines after a shareholder–creditor merger. We also report strong, robust evidence that the negative impact of mergers on firms' expected crash risk increases when institutional investors or lenders have a greater stake in the treatment firms or when shareholder–creditor conflicts are apt to be exacerbated. Additionally, we document that firms issue management earnings forecasts (especially bad news forecasts) more frequently after these mergers. Finally, we find that expected crash risk decreases more after mergers in firms suffering worse information asymmetry and with weak monitoring mechanisms. Our evidence suggests that option market participants value the dual holder's role in deterring managers' bad news hoarding.

Foreign workers have been an important part of the labor force in public accounting firms over the past two decades. In this paper, we investigate whether and why foreign workers influence audit quality. We find that audit offices with more newly hired foreign labor have a lower mean absolute value of discretionary accruals and a smaller rate of restatements for their clients. The effect is more pronounced for audit offices that face more resource constraints or require greater foreign expertise. The results of improved audit quality are robust to alternative measures of immigrant intensity and audit quality, alternative samples, and using different ways to address endogeneity concerns. Overall, our paper contributes to the literature by showing the impact of foreign labor in the auditing profession and provides public policy implications for the recent H‐1B visa debate.

Exclusions from street earnings can include both expected exclusions, forecasted ex ante by analysts, and unexpected exclusions, revealed after earnings are reported. While prior research largely examines total exclusions from street earnings, unexpected exclusions reflect the news or surprise in exclusions. We investigate the properties and informativeness of unexpected exclusions for future profitability, benchmark beating, analyst forecast errors, and future stock returns. We find that unexpected exclusions represent a mix of transitory and recurring items and are informative about future street earnings. In an analysis of hand‐collected analysts' reports, we find that unexpected exclusions are more likely to reflect misestimated recurring items when analysts forecasted exclusions, and unexpected transitory items when analysts did not forecast exclusions. We also examine benchmark‐beating behavior, in which street earnings meet street forecasts but GAAP earnings miss GAAP forecasts. We observe that benchmark beating is more likely to occur when analysts forecast exclusions than when they do not. Moreover, we find unexpected exclusions are more persistent when street earnings meet street forecasts but GAAP earnings miss GAAP forecasts. These findings are consistent with recurring earnings amounts being opportunistically shifted to excluded items to meet analysts' street forecasts. Finally, we find some evidence that analysts and investors react to, but do not fully incorporate, the information in unexpected exclusions, based on forecast revisions and stock price reactions.